Cannot using examples.models.llama.export_llama due to incorrect deprecated

[hsyodyssey]

🐛 Describe the bug

cannot using:

python -m examples.models.llama.export_llama   --checkpoint "checkpoint.pth"   --params "original_params.json"   -kv   --use_sdpa_with_kv_cache   -X   -d bf16   --metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001]}'   --output_name="llama3_2.pte"

With Error

  File "/home/repos/executorch/exir/passes/sym_shape_eval_pass.py", line 14, in <module>
    from executorch.exir._warnings import deprecated
  File "/home/repos/executorch/exir/_warnings.py", line 29, in <module>
    class experimental(deprecated):
TypeError: function() argument 'code' must be code, not str

Versions

PyTorch version: 2.6.0.dev20241007+cpu
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.2 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 18.0.1 (https://android.googlesource.com/toolchain/llvm-project d8003a456d14a3deb8054cdaa529ffbf02d9b262)
CMake version: version 3.27.7
Libc version: glibc-2.35

Python version: 3.10.0 (default, Mar 3 2022, 09:58:08) [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4090
Nvidia driver version: 560.94
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 24
On-line CPU(s) list: 0-23
Vendor ID: GenuineIntel
Model name: 13th Gen Intel(R) Core(TM) i7-13700K
CPU family: 6
Model: 183
Thread(s) per core: 2
Core(s) per socket: 12
Socket(s): 1
Stepping: 1
BogoMIPS: 6835.20
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology tsc_reliable nonstop_tsc cpuid pni pclmulqdq vmx ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves avx_vnni umip waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize flush_l1d arch_capabilities
Virtualization: VT-x
Hypervisor vendor: Microsoft
Virtualization type: full
L1d cache: 576 KiB (12 instances)
L1i cache: 384 KiB (12 instances)
L2 cache: 24 MiB (12 instances)
L3 cache: 30 MiB (1 instance)
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] executorch==0.5.0a0+af13be9
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu11==11.10.3.66
[pip3] nvidia-cublas-cu12==12.1.3.1
[pip3] nvidia-cuda-cupti-cu11==11.7.101
[pip3] nvidia-cuda-cupti-cu12==12.1.105
[pip3] nvidia-cuda-nvrtc-cu11==11.7.99
[pip3] nvidia-cuda-nvrtc-cu12==12.1.105
[pip3] nvidia-cuda-runtime-cu11==11.7.99
[pip3] nvidia-cuda-runtime-cu12==12.1.105
[pip3] nvidia-cudnn-cu11==8.5.0.96
[pip3] nvidia-cudnn-cu12==8.9.2.26
[pip3] nvidia-cufft-cu11==10.9.0.58
[pip3] nvidia-cufft-cu12==11.0.2.54
[pip3] nvidia-curand-cu11==10.2.10.91
[pip3] nvidia-curand-cu12==10.3.2.106
[pip3] nvidia-cusolver-cu11==11.4.0.1
[pip3] nvidia-cusolver-cu12==11.4.5.107
[pip3] nvidia-cusparse-cu11==11.7.4.91
[pip3] nvidia-cusparse-cu12==12.1.0.106
[pip3] nvidia-nccl-cu11==2.14.3
[pip3] nvidia-nccl-cu12==2.18.1
[pip3] nvidia-nvjitlink-cu12==12.3.52
[pip3] nvidia-nvtx-cu11==11.7.91
[pip3] nvidia-nvtx-cu12==12.1.105
[pip3] torch==2.6.0.dev20241007+cpu
[pip3] torchao==0.5.0+git0916b5b2
[pip3] torchaudio==2.5.0.dev20241007+cpu
[pip3] torchsr==1.0.4
[pip3] torchvision==0.20.0.dev20241007+cpu
[pip3] triton==3.1.0
[conda] executorch 0.5.0a0+af13be9 pypi_0 pypi
[conda] numpy 1.26.4 pypi_0 pypi
[conda] torch 2.6.0.dev20241007+cpu pypi_0 pypi
[conda] torchao 0.5.0+git0916b5b2 pypi_0 pypi
[conda] torchaudio 2.5.0.dev20241007+cpu pypi_0 pypi
[conda] torchsr 1.0.4 pypi_0 pypi
[conda] torchvision 0.20.0.dev20241007+cpu pypi_0 pypi
[conda] triton 3.1.0 pypi_0 pypi

cc @mergennachin @cccclai @helunwencser @dvorjackz

[dbort]

It's hard to tell without the full stack trace, but this may be a problem with the @deprecated decoration at

executorch/exir/passes/sym_shape_eval_pass.py

Line 169 in af13be9

@deprecated(

Added in #5033 cc: @JacobSzwejbka

[hsyodyssey]

It's hard to tell without the full stack trace, but this may be a problem with the @deprecated decoration at

executorch/exir/passes/sym_shape_eval_pass.py

Line 169 in af13be9

@deprecated(

Added in #5033 cc: @JacobSzwejbka

yeah, I think so.

[jackzhxng]

The error is saying that deprecated isn't a class, so you can't subclass it. deprecated was changed from a function to a class here - python/typing_extensions#302, so you might want to see if you have an old version of typing_extensions.